code-review

A structured checklist and process for examining TypeScript, Node.js, infrastructure, and full-stack web code.

In plain words
What is it for?
Reviewing code changes, pull requests, or parts of a codebase, including checks for input validation, secrets, error handling, types, database queries, and file-path safety.
Why use it?
It helps find logic errors, security risks, performance problems, and maintenance issues that may be missed during a casual review.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/espennilsen/pi/code-review
Any agent
npx skills add espennilsen/pi --skill code-review
Clone the repo
git clone --depth 1 https://github.com/espennilsen/pi

Made for: Claude Code, Codex.

Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 721 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00048 $0.00721
Opus 5 $0.00024 $0.00360
Sonnet 5 $0.00010 $0.00144
Haiku 4.5 $0.00005 $0.00072

Measured 3d ago against content hash 1cd20c92dc59, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/code-review/SKILL.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Review

Systematic code review for Espen's TypeScript/Node.js projects.

Process

  1. Understand scope — Read the changed files or the area under review:

    # For git changes
    git diff --name-only HEAD~1
    git diff HEAD~1
    
    # For a specific area
    find src/ -name "*.ts" -newer <reference-file>
    
  2. Read the code — Use the read tool on each file. Don't guess.

  3. Analyze against checklist — Score each category.

  4. Report — Use the output format below.

Review Checklist

Correctness

  • Logic handles edge cases (null, empty, boundary values)
  • Error handling is explicit (no swallowed errors, no bare catch {})
  • Async code handles rejection/cancellation properly
  • Types are accurate (no unnecessary any, proper narrowing)

Security

  • No secrets or credentials in code
  • User input is validated/sanitized before use
  • SQL queries use parameterized statements (no string interpolation)
  • File paths are resolved safely (no path traversal)
  • Auth checks are present where needed

Performance

  • No N+1 queries or unbounded loops over large datasets
  • Heavy operations are async or streamed (not blocking)
  • Database queries use appropriate indexes
  • Large responses are paginated or truncated

Maintainability

  • Functions do one thing with clear names
  • No magic numbers or hardcoded values that should be config
  • Types and interfaces are defined (not inline object shapes)
  • Dead code and unused imports are removed
  • Comments explain why, not what

Project Conventions

  • Follows existing patterns in the codebase
  • File naming and directory structure is consistent
  • Error messages are helpful for debugging
  • Logging is appropriate (not too noisy, not silent on errors)

Output Format

## Code Review: [scope]

### Summary
One paragraph: what the code does, overall quality assessment.

### Issues

#### 🔴 Critical
- [file:line] Description and fix

#### 🟡 Important
- [file:line] Description and suggestion

#### 🔵 Minor
- [file:line] Nit or style suggestion

### What's Good
- Call out well-written code, good patterns, clever solutions

### Recommendations
- Prioritized list of changes, starting with most impactful

Read the full file on GitHub · 97 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 97 lines · 48 tokens per session scan A 1cd20c92dc59

Subscribe to this mod's changes

code-review is a skill published in the GitHub repository espennilsen/pi (117 stars, last pushed 10d ago), licensed MIT. It adds 48 tokens to every session and 721 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens